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My Smartwatch Is Mine — Machine Learning Based Theft Detection of Smartwatches

机译:我的Smartwatch是我的-基于机器学习的Smartwatch盗窃检测

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Smartwatches are small but powerful devices which make daily life easier and are without a doubt desirable objects for thieves. In this paper, we present a first machine learning based theft detection approach running in a user's domain, relying solely on data of his smartwatch and thus not involving third parties. Hence, we collect data from multiple persons to first show that there is an exploitable structure within data provided by a smartwatch's inertial sensors and perform user identification on the basis of that data. Then we will present and thoroughly evaluate our robust, efficient and fast (within seconds) theft detection algorithm which has both a low false rejection rate and an even lower false acceptance rate.
机译:智能手表是小型但功能强大的设备,可以使日常生活更轻松,并且无疑是小偷想要的物品。在本文中,我们提出了第一种基于机器学习的盗窃检测方法,该方法在用户的域中运行,仅依赖于其智能手表的数据,因此不涉及第三方。因此,我们从多个人那里收集数据,首先显示出智能手表的惯性传感器提供的数据中存在可利用的结构,并根据该数据执行用户识别。然后,我们将介绍并彻底评估我们的鲁棒,有效和快速(几秒钟之内)的盗窃检测算法,该算法具有较低的错误拒绝率和更低的错误接受率。

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